Data Scientist

hiring a Data Scientist

You’re a great fit if you:

• Have a strong background in

  data science, machine learning, or applied statistics

  .
• Are proficient in

  Python, SQL

  , and familiar with libraries such as

  Pandas, NumPy, Scikit-learn, and PyTorch/TensorFlow

  .
• Understand

  probabilistic modeling, statistical inference, and experimentation frameworks (A/B testing, causal inference)

  .
• Can

  collect, clean, and transform complex datasets

  into structured formats ready for modeling and analysis.
• Have experience designing and evaluating

  predictive models

  , using metrics like precision, recall, F1-score, and ROC-AUC.
• Are comfortable working with

  large-scale data systems

  (Snowflake, BigQuery, or similar).
• Are curious about

  AI agents

  , and how data can shape the reasoning, adaptability, and behavior of intelligent systems.
• Enjoy

  collaborating with cross-functional teams

  — from engineers to research scientists — to define meaningful KPIs and experiment setups.

Primary Goal of This Role

To design and implement robust data models, pipelines, and metrics that support experimentation, benchmarking, and continuous learning for agentic AI systems. The role focuses on building data-driven insights into how agents reason, perform, and improve over time across algorithmic and real-world tasks.

What You’ll Do

• Develop

  data collection and preprocessing pipelines

  for structured and unstructured data from multiple agent simulations.
• Build and iterate on

  machine learning models

  for performance prediction, behavior clustering, and outcome optimization.
• Design and maintain

  dashboards and visualization tools

  for monitoring agent performance, benchmarks, and trends.
• Conduct

  statistical analyses

  to evaluate the efficacy of AI systems under various environments and constraints.
• Collaborate with engineers to design

  evaluation frameworks

  that measure reasoning quality, adaptability, and efficiency.
• Prototype

  data-driven tools and feedback loops

  to automatically improve model accuracy and agent behavior over time.
• Work closely with AI research teams to

  translate experimental results

  into scalable, production-grade insights.

Why This Role Is Exciting

• Work at the forefront of

  AI agent intelligence

  and help define how data shapes their evolution.
• Blend

  machine learning, experimentation, and data engineering

  in one role.
• Collaborate with top-tier AI engineers on

  new agent benchmarks and feedback mechanisms

  .
• Contribute to a mission that merges

  algorithmic reasoning, real-world performance, and human-like decision-making

  .

Pay & Work Structure

• You’ll be classified as an

  hourly contractor

• Paid weekly

  via Stripe Connect, based on hours logged.

• Part-time (20 hrs - 40 hrs/week)

  with fully remote, async flexibility — work from anywhere, on your own schedule.
• Weekly bonus of $500 - $1000 USD per 5 task created.